Since the first railway station choice studies of the 1970s, a substantial body of research on the topic has been completed, primarily in North America, the UK and the Netherlands. With many countries seeing sustained growth in rail passenger numbers, which is forecast to continue, station choice models have an important role to play in assessing proposals for new stations or service changes. This paper reviews the modelling approaches adopted, the factors found to influence station choice, and the application of models to real-world demand forecasting scenarios. A consensus has formed around using the closed-form multinomial logit and nested logit models, with limited use of more advanced simulation-based models, and the direction effects of a range of factors have been consistently reported. However, there are questions over the validity of applying non-spatial discrete choice models to a context where spatial correlation will be present, in particular with regard to the models' ability to adequately represent the abstraction behaviours resulting from competition between stations. Furthermore, there has been limited progress towards developing a methodology to integrate a station choice element into the aggregate models typically used to forecast passenger demand for new stations.
opentripplanner provides functions that enable multi-modal routing in R. It provides an interface to the OpenTripPlanner (OTP) Java routing service, which allows calculation of routes on large transport networks, locally or via calls to a remote server. The package contains three groups of functions for: (1) setting up and managing a local instance of OTP;(2) connecting to OTP locally or remotely; and (3) sending requests to the OTP API and importing the results and converting them into appropriate classes for further analysis.
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